Integrated intra‐ and intercellular signaling knowledge for multicellular omics analysis.

Molecular knowledge of biological processes is a cornerstone in omics data analysis. Applied to single‐cell data, such analyses provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources covering interactions and roles of proteins in inter‐ and intracellular signaling, as well as transcriptional and post‐transcriptional regulation. We added protein complex information and annotations on function, localization, and role in diseases for each protein. The resource is available for human, and via homology translation for mouse and rat. The data are accessible via OmniPath's web service (https://omnipathdb.org/), a Cytoscape plug‐in, and packages in R/Bioconductor and Python, providing access options for computational and experimental scientists. We created workflows with tutorials to facilitate the analysis of cell–cell interactions and affected downstream intracellular signaling processes. OmniPath provides a single access point to knowledge spanning intra‐ and intercellular processes for data analysis, as we demonstrate in applications studying SARS‐CoV‐2 infection and ulcerative colitis. SYNOPSIS: Over 100 resources are integrated into OmniPath, a comprehensive knowledge base of intra‐ and inter‐cellular signaling. Workflows are provided and illustrated in case studies analyzing omics data in SARS‐CoV‐2 infection and ulcerative colitis. OmniPath includes 4,000,000 annotations for over 20,000 proteins.A new framework defining transmitter and receiver roles generalizes the concepts of ligand and receptor.Integrated analysis of intra‐ and intercellular signaling can be performed to study how cells affect each other in healthy and diseased conditions.Software tools and workflows in R and Python facilitate the analysis of bulk and single‐cell omics data using tools such as CellPhoneDB, NicheNet and CARNIVAL. [ABSTRACT FROM AUTHOR]